Application of ameliorative whale optimization algorithm to optimal allocation of multi-objective water resources
In order to make whale optimization algorithm (WOA) better to solve the complicated problem from the optimal allocation of multi-objective water resources,the location of the population is initialized with Logistic mapping for enhancing the quality of the initialized location of population at first,and then inertia weight is added to enhance the local search ability,so as to realize the amelioration of WOA.Secondly,the ameliorative whale optimization algorithm (AWOA) is applied to the Handan water resources optimal allocation model which takes the maximizations of both the economic benefit and social benefit (the minimization of water shortage) therein as its target.At last,by taking solving the obtained minimization of water shortage in the Pareto front as the special preference,the iterative processes and the solving results of AWOA,WOA and particle swarm optimization (PSO) are compared and analyzed.In the aspect of the iterative process,AWOA has a faster converging speed than that of PSO and WOA,in which the converging speed of WOA is the slowest.The analysis on the iterative results shows that both the economic benefit and social benefit obtained from AWOA are better than those got from WOA and PSO.Therefore,both the converging speed and converging accuracy of AWOA are largely enhanced,thus it is feasible and effective to be applied to solve the optimal allocation of multi-objective water resources.
water resourcesoptimal allocationAWOAminimization of water shortage
国家科技期刊平台
NSTL
万方数据
维普
